Weifeng Gu
Impact in
- Aging top 0.1%
- Genetics, Aging, and Longevity in Model Organisms
- Molecular Biology top 2%
- CRISPR and Genetic Engineering
- RNA Research and Splicing
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- Epigenetics and DNA Methylation
Papers in
-
- RNA Research and Splicing 14
- RNA modifications and cancer 14
- CRISPR and Genetic Engineering 13
- RNA and protein synthesis mechanisms 9
- Aging 11
- Genetics, Aging, and Longevity in Model Organisms 11
- Co-authors
- Craig C. Mello (19 shared papers)Darryl Conte (11 shared papers)Masaki Shirayama (8 shared papers)Heng-Chi Lee (4 shared papers)Daniel A. Chaves (6 shared papers)Pedro J. Batista (6 shared papers)Julie M. Claycomb (6 shared papers)Elaine M. Youngman (4 shared papers)
- Journals
- Cell (5 papers)Molecular Cell (5 papers)RNA (4 papers)Current Biology (2 papers)Biochemical Journal (2 papers)
- Partner nations
- United StatesPortugalChina
In The Last Decade
Weifeng Gu
41 papers receiving 4.6k citations
Peers
Comparison fields: 5 of 113
- Aging 1.3k
- Molecular Biology 3.8k
- Cancer Research 600
- Plant Science 1.4k
- Endocrinology 130
Countries citing papers authored by Weifeng Gu
This map shows the geographic impact of Weifeng Gu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Weifeng Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weifeng Gu more than expected).
Fields of papers citing papers by Weifeng Gu
This network shows the impact of papers produced by Weifeng Gu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Weifeng Gu. The network helps show where Weifeng Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Weifeng Gu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 441 | |
| 2 | 2012 | 438 | |
| 3 | 2006 | 397 | |
| 4 | 2009 | 384 | |
| 5 | 2009 | 339 | |
| 6 | 2012 | 287 | |
| 7 | 2010 | 272 | |
| 8 | 2018 | 185 | |
| 9 | 2013 | 179 | |
| 10 | 2010 | 176 | |
| 11 | 2012 | 169 | |
| 12 | 2010 | 150 | |
| 13 | 2001 | 146 | |
| 14 | 2013 | 130 | |
| 15 | 2001 | 105 | |
| 16 | 2012 | 94 | |
| 17 | 2003 | 93 | |
| 18 | 2019 | 82 | |
| 19 | 2005 | 81 | |
| 20 | 2015 | 61 |
About Weifeng Gu
Weifeng Gu is a scholar working on Molecular Biology, Aging, Plant Science, Cancer Research and Rehabilitation, having authored 41 papers that have together received 4.6k indexed citations. Recurring topics across this work include RNA Research and Splicing (14 papers), RNA modifications and cancer (14 papers), CRISPR and Genetic Engineering (13 papers), Genetics, Aging, and Longevity in Model Organisms (11 papers), RNA and protein synthesis mechanisms (9 papers), Chromosomal and Genetic Variations (8 papers), MicroRNA in disease regulation (4 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Aging (1.3k citations), Molecular Biology (3.8k citations), Cancer Research (600 citations), Plant Science (1.4k citations) and Endocrinology (130 citations). Weifeng Gu has collaborated with scholars based in United States, Portugal and China. Frequent co-authors include Craig C. Mello, Darryl Conte, Masaki Shirayama, Heng-Chi Lee, Daniel A. Chaves, Pedro J. Batista, Julie M. Claycomb, Elaine M. Youngman, Takao Ishidate and Meetu Seth. Their work appears in journals such as Cell, Molecular Cell, RNA, Current Biology and Biochemical Journal.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.